• Journal of the Korean Society of Safety
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• v.39 no.3
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• pp.75-83
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• 2024

Accurately assessing and managing risks in any endeavor is crucial. Risk assessment in engineering translates the abstract concept of risk into actionable strategies for systematic risk management. However, risk validation is met with significant skepticism, particularly concerning the uncertainty of probability. This study aims to address the aforementioned uncertainty in a multitude of ways. Firstly, instead of relying on deterministic probability, it acknowledges uncertainty and presents a probabilistic interval. Secondly, considering the uncertainty interval highlighted in OREDA, it delineates the bounds of the probabilistic interval. Lastly, it investigates how much explanatory power deterministic probability has within the defined probabilistic interval. By utilizing fault tree analysis (FTA) and integrating confidence intervals, a probabilistic risk assessment was conducted to scrutinize the explanatory power of deterministic probability. In this context, explanatory power signifies the proportion of probability within the probabilistic risk assessment interval that lies below the deterministic probability. Research results reveal that at a 90% confidence interval, the explanatory power of deterministic probability decreases to 73%. Additionally, it was confirmed that explanatory power reached 100% only with a probability application 36.9 times higher.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2151-2161
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• 2021

Nuclear data (ND) sensitivity and uncertainty (S/U) quantification in shielding applications is performed using deterministic and probabilistic approaches. In this paper the validation of the newly developed deterministic program package ASUSD (ADVANTG + SUSD3D) is presented. ASUSD was developed with the aim of automating the process of ND S/U while retaining the computational efficiency of the deterministic approach to ND S/U analysis. The paper includes a detailed description of each of the programs contained within ASUSD, the computational workflow and validation results. ASUSD was validated on two shielding benchmark experiments from the Shielding Integral Benchmark Archive and Database (SINBAD) - the fission relevant ASPIS Iron 88 experiment and the fusion relevant Frascati Neutron Generator (FNG) Helium Cooled Pebble Bed (HCPB) Test Blanket Module (TBM) mock-up experiment. The validation process was performed in two stages. Firstly, the Denovo discrete ordinates transport solver was validated as a standalone solver. Secondly, the ASUSD program package as a whole was validated as a ND S/U analysis tool. Both stages of the validation process yielded excellent results, with a maximum difference of 17% in final uncertainties due to ND between ASUSD and the stochastic ND S/U approach. Based on these results, ASUSD has proven to be a user friendly and computationally efficient tool for deterministic ND S/U analysis of shielding geometries.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.502-506
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• 2013

The cash flow forecasting is normally done by contractors in construction industry at early stages of the project for contractual decisions. The decision making in such situations involve uncertainty about future cash flows and assessment of working capital requirements gains more importance in projects constrained by cash. The traditional approach to assess the working capital requirements is deterministic in and neglects the uncertainty. This paper presents an alternate approach to assessment of working capital requirements for contractor based on fuzzy set theory by considering the uncertainty and ambiguity involved at payment periods. Statistical methods are used to deal with the uncertainty for working capital curves. Membership functions of the fuzzy sets are developed based on these statistical measures. Advantage of fuzzy peak working capital requirements is demonstrated using peak working capital requirements curves. Fuzzy peak working capital requirements curves are compared with deterministic curves and the results are analyzed. Fuzzy weighted average methodology is proposed for the assessment of peak working capital requirements.

• Geomechanics and Engineering
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• v.3 no.2
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• pp.153-167
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• 2011

Traditional design methods of bearing capacity of shallow foundations are deterministic in the sense that they do not explicitly consider the inherent uncertainty associated with the factors affecting bearing capacity. To account for such uncertainty, available deterministic methods rather employ a fixed global factor of safety that may lead to inappropriate bearing capacity predictions. An alternative stochastic approach is essential to provide a more rational estimation of bearing capacity. In this paper, the likely distribution of predicted bearing capacity of strip footings subjected to vertical loads is obtained using a stochastic approach based on the Monte Carlo simulation. The approach accounts for the uncertainty associated with the soil shear strength parameters: cohesion, c, and friction angle, ${\phi}$, and the cross correlation between c and ${\phi}$. A set of stochastic design charts that assure target reliability levels of 90% and 95%, are developed for routine use by practitioners. The charts negate the need for a factor of safety and provide a more reliable indication of what the actual bearing capacity might be.

• Nuclear Engineering and Technology
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• v.40 no.5
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• pp.327-348
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• 2008

A risk-informed regulatory approach implies that risk insights be used as supplement of deterministic information for safety decision-making purposes. In this view, the use of risk assessment techniques is expected to lead to improved safety and a more rational allocation of the limited resources available. On the other hand, it is recognized that uncertainties affect both the deterministic safety analyses and the risk assessments. In order for the risk-informed decision making process to be effective, the adequate representation and treatment of such uncertainties is mandatory. In this paper, the risk-informed regulatory framework is considered under the focus of the uncertainty issue. Traditionally, probability theory has provided the language and mathematics for the representation and treatment of uncertainty. More recently, other mathematical structures have been introduced. In particular, the Dempster-Shafer theory of evidence is here illustrated as a generalized framework encompassing probability theory and possibility theory. The special case of probability theory is only addressed as term of comparison, given that it is a well known subject. On the other hand, the special case of possibility theory is amply illustrated. An example of the combination of probability and possibility for treating the uncertainty in the parameters of an event tree is illustrated.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.1426-1433
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• 2005

In this paper, reliability analysis of surface settlement by ground water drawdown is performed using a reliability-groundwater flow numerical model. The result is compared with that of the deterministic model to evaluate the influence of the uncertainty from hydraulic conductivity in the soft ground as well as to determine the range of hydraulic conductivity of grouted ground. From the analyses, it was found that probability of failure to exceed the tolerable settlement was very high, if the hydraulic conductivity of grouted ground is decided from the deterministic flow model only. Reliability analysis which evaluates variance of hydraulic conductivity should be used together with the deterministic model for grouting design of tunnels to prevent ground water drawdown.

• Nuclear Engineering and Technology
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• v.47 no.3
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• pp.306-314
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• 2015

This paper examines the difference in the value of the nuclear fuel cycle cost calculated by the deterministic and probabilistic methods on the basis of an equilibrium model. Calculating using the deterministic method, the direct disposal cost and Pyro-SFR (sodium-cooled fast reactor) nuclear fuel cycle cost, including the reactor cost, were found to be 66.41 mills/kWh and 77.82 mills/kWh, respectively (1 mill = one thousand of a dollar, i.e., $10^{-3}$ $). This is because the cost of SFR is considerably expensive. Calculating again using the probabilistic method, however, the direct disposal cost and Pyro-SFR nuclear fuel cycle cost, excluding the reactor cost, were found be 7.47 mills/kWh and 6.40 mills/kWh, respectively, on the basis of the most likely value. This is because the nuclear fuel cycle cost is significantly affected by the standard deviation and the mean of the unit cost that includes uncertainty. Thus, it is judged that not only the deterministic method, but also the probabilistic method, would also be necessary to evaluate the nuclear fuel cycle cost. By analyzing the sensitivity of the unit cost in each phase of the nuclear fuel cycle, it was found that the uranium unit price is the most influential factor in determining nuclear fuel cycle costs.

• The Korean Journal of Applied Statistics
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• v.33 no.2
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• pp.185-201
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• 2020

Scenario population projection reflects the high probability of future realization and ease of statistical interpretation. Statistics Korea (2019) also presents the results of 30 combinations, including special scenarios, as official statistics. However, deterministic population projections provide limited information about future uncertainties with several limitations that are not probabilistic. The deterministic population projections are scenario-based estimates and show a perfect autocorrelation of three factors (birth, death, movement) of population variation over time. Therefore, international organizations UN, the Max Planck Population Research Institute (MPIDR) of Germany and the Vienna Population Research Institute (VID) of Austria have suggested stochastic based population estimates. In addition, some National Statistics Offices have also adopted this method to provide information along with the scenario results. This paper calculates the demographics of Korea based on a probabilistic or stochastic basis and then draws the pros and cons and show implications of the scenario (deterministic) population projections.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2009.06a
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• pp.186-186
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• 2009

The characterization strategy of fracture networks are classified into a deterministic or statistical characterization according to the type of required information. A deterministic characterization is most efficient for a sparsely fractured system, while the statistics are sufficient for densely fractured rock. In this study, the ensemble mean and variability of the effective connectivity is systematically analyzed with various density values for different network structures of a power law size distribution. The results of high resolution Monte Carlo analyses show that statistical characteristics can be a necessary information to determine the transport properties of a fracture system when fracture density is greater than a percolation threshold. When the percolation probability (II) approaches unity with increasing fracture density, the effective connectivity of the network can be safely estimated using statistics only (sufficient condition). It is inferred from conditional simulations that deterministic information for main pathways can reduce the uncertainty in estimation of system properties when the network becomes denser. Overall results imply that most pathways need to be identified when II < 0.5 statistics are sufficient when II $\rightarrow$ 1 and statistics are necessary and the identification of main pathways can significantly reduce the uncertainty in estimation of transport properties when 0.5$\ll$1. It is suggested that the proper estimation of the percolation probability of a fracture network is a prerequisite for an appropriate conceptualization and further characterization.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.4
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• pp.665-672
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• 2010

This paper describes Monte Carlo Simulation(MCS) to assess the uncertainty of dynamic pressure calibrator and the expanded uncertainty results that were compared by GUM approximation and MCS. MCS uncertainties were computed using defining a domain of possible inputs, generating inputs randomly using probability distribution, performing a deterministic computation repeatedly and aggregating the results. It was revealed that the expanded uncertainty between GUM and MCS was different from each other. the expanded uncertainties were 0.5366%, 0.4856%, respectively. MCS is a suitable method for determining the uncertainty of simple and complex measurement systems. It should be more widely used and studied in measurement uncertainty calculations.